Ensembles for Class Imbalance Problems in Various Domains

Abstract

The paper is an analysis of class imbalance problems from various domains such as the medical field, sentiment analysis, software de-fects, water portability, and relationship status of students and summarizes the performance of data resampling techniques such as random undersampling and oversampling. Synthetic minority oversampling techniques combined with the power of ensemble methods such as bagging, boosting, and hybrid techniques are generally used to solve the class imbalance problem.